## Readme file for replication of Dahlgaard (2016):

## replication files for main article

"forcegen_bootstrap.r" takes the data and creates the main forcing variable by a bootstrap procedure similar to Kotakorpi et al. 

"dataan.r" takes the data and produces the table of descriptive statistics (Table 1), the table with N per step (Table 2), figures 2 and 3, and the table with main results (Table 3)

"dataan.r" takes the data and produces the table of descriptive statistics (Table 1), the table with N per step (Table 2), figures 2 and 3, and the table with main results (Table 3)

"dataan_by_year.r" produces figure 4, effects split by election. 

"rob1.r" takes the data and estimates the effect when the bandwidth is varied (figure 5)

"party_desc.r" creates table 4 with descriptives of parties running on open lists and not. 

## replication files for Supporting Information

"plac1.r" takes the data and produces placebo tests at mock thresholds (figure S.1)

"plac2.r" takes the data and estimates the effect on past incumbency (figure S.2)

"rob2.r" takes the data and estimates the effect with different bandwidths and specifications (figure S.3))

"rob3.r" takes the data and estimates the effect using an alternative forcing variable (Table S.1)

"datacr.r" creates the alternative forcing variable used in "rob4.r"¨

"rob4.r" takes the data and estimates the effect using an alternative forcing variable (Table S.2)

“rob_rank.r” only compares outcomes between the candidates just above and just below the cutoff without considering their distance to it. (Table S.3)